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Bayesian reasoning and machine learning

Bayesian reasoning and machine learning (Loan 18 times)

Material type
단행본
Personal Author
Barber, David, 1968-.
Title Statement
Bayesian reasoning and machine learning / David Barber.
Publication, Distribution, etc
Cambridge ;   New York :   Cambridge University Press,   c2012.  
Physical Medium
xxiv, 697 p. : ill. ; 26 cm.
ISBN
9780521518147 (hbk.)
Bibliography, Etc. Note
Includes bibliographical references (p. [675]-688) and index.
Subject Added Entry-Topical Term
Machine learning. Bayesian statistical decision theory.
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001 000045740418
005 20140326180454
008 120412s2012 enka b 001 0 eng
020 ▼a 9780521518147 (hbk.)
035 ▼a (KERIS)BIB000012796883
040 ▼a 211032 ▼c 211032 ▼d 244002 ▼d 211009
050 0 0 ▼a QA267 ▼b .B347 2012
082 0 0 ▼a 006.3/1 ▼2 23
084 ▼a 006.31 ▼2 DDCK
090 ▼a 006.31 ▼b B234b
100 1 ▼a Barber, David, ▼d 1968-.
245 1 0 ▼a Bayesian reasoning and machine learning / ▼c David Barber.
260 ▼a Cambridge ; ▼a New York : ▼b Cambridge University Press, ▼c c2012.
300 ▼a xxiv, 697 p. : ▼b ill. ; ▼c 26 cm.
504 ▼a Includes bibliographical references (p. [675]-688) and index.
650 0 ▼a Machine learning.
650 0 ▼a Bayesian statistical decision theory.

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No. 1 Location Science & Engineering Library/Sci-Info(Stacks2)/ Call Number 006.31 B234b Accession No. 121229289 Availability In loan Due Date 2022-10-21 Make a Reservation Available for Reserve R Service M
No. 2 Location Sejong Academic Information Center/Science & Technology/ Call Number 006.31 B234b Accession No. 151314923 Availability Available Due Date Make a Reservation Service M
No. Location Call Number Accession No. Availability Due Date Make a Reservation Service
No. 1 Location Science & Engineering Library/Sci-Info(Stacks2)/ Call Number 006.31 B234b Accession No. 121229289 Availability In loan Due Date 2022-10-21 Make a Reservation Available for Reserve R Service M
No. Location Call Number Accession No. Availability Due Date Make a Reservation Service
No. 1 Location Sejong Academic Information Center/Science & Technology/ Call Number 006.31 B234b Accession No. 151314923 Availability Available Due Date Make a Reservation Service M

Contents information

Table of Contents

Preface
Part I. Inference in Probabilistic Models:
1. Probabilistic reasoning
2. Basic graph concepts
3. Belief networks
4. Graphical models
5. Efficient inference in trees
6. The junction tree algorithm
7. Making decisions
Part II. Learning in Probabilistic Models:
8. Statistics for machine learning
9. Learning as inference
10. Naive Bayes
11. Learning with hidden variables
12. Bayesian model selection
Part III. Machine Learning:
13. Machine learning concepts
14. Nearest neighbour classification
15. Unsupervised linear dimension reduction
16. Supervised linear dimension reduction
17. Linear models
18. Bayesian linear models
19. Gaussian processes
20. Mixture models
21. Latent linear models
22. Latent ability models
Part IV. Dynamical Models:
23. Discrete-state Markov models
24. Continuous-state Markov models
25. Switching linear dynamical systems
26. Distributed computation
Part V. Approximate Inference:
27. Sampling
28. Deterministic approximate inference
Appendix. Background mathematics
Bibliography
Index.

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